Kyle E. C. Booth
YOU?
Author Swipe
Quadratic unconstrained binary optimization and constraint programming approaches for lattice-based cyclic peptide docking Open
The peptide-protein docking problem is an important problem in structural biology that facilitates rational and efficient drug design. In this work, we explore modeling and solving this problem with the quantum-amenable quadratic unconstra…
Optimization of Next-Day Delivery Coverage using Constraint Programming and Random Key Optimizers Open
We consider the logistics network of an e-commerce retailer, specifically the so-called "middle mile" network, that routes inventory from supply warehouses to distribution stations to be ingested into the terminal ("last mile") delivery ne…
Quadratic unconstrained binary optimization and constraint programming\n approaches for lattice-based cyclic peptide docking Open
The peptide-protein docking problem is an important problem in structural\nbiology that facilitates rational and efficient drug design. In this work, we\nexplore modeling and solving this problem with the quantum-amenable quadratic\nuncons…
Solving QUBOs with a quantum-amenable branch and bound method Open
Due to the expected disparity in quantum vs. classical clock speeds, quantum advantage for branch and bound algorithms is more likely achievable in settings involving large search trees and low operator evaluation costs. Therefore, in this…
Constraint programming models for depth-optimal qubit assignment and SWAP-based routing Open
Due to the limited connectivity of gate model quantum devices, logical quantum circuits must be compiled to target hardware before they can be executed. Often, this process involves the insertion of SWAP gates into the logical circuit, usu…
Quantum-accelerated constraint programming Open
Constraint programming (CP) is a paradigm used to model and solve constraint satisfaction and combinatorial optimization problems. In CP, problems are modeled with constraints that describe acceptable solutions and solved with backtracking…
View article: Learning Scheduling Models from Event Data
Learning Scheduling Models from Event Data Open
A significant challenge in declarative approaches to scheduling is the creation of a model: the set of resources and their capacities and the types of activities and their temporal and resource requirements. In practice, such models are de…
Comparing and Integrating Constraint Programming and Temporal Planning for Quantum Circuit Compilation Open
Recently, the makespan-minimization problem of compiling a general class of quantum algorithms into near-term quantum processors has been introduced to the AI community. The research demonstrated that temporal planning is a strong approach…
Robots in Retirement Homes: Person Search and Task Planning for a Group of Residents by a Team of Assistive Robots Open
The authors present a general multirobot task planning and execution architecture for a team of heterogeneous mobile robots that interact with multiple human users. The designed architecture is implemented in an environment where such robo…
View article: Table of contents
Table of contents Open
perceive, reason, learn, and act intelligently.
Mixed-Integer and Constraint Programming Techniques for Mobile Robot Task Planning Open
This paper was recommended for publication by Editor J. Li upon evaluation of the Associate Editor and Reviewers’ comments.